server/guardrails/customer_service.py implements the Guardrail interface with
the v0.1 Customer Service ruleset (RESEARCH.md safety baseline): blocks
legal/financial/medical advice, real-company impersonation, and a debrief
output filter that blocks recommendations the learner advise legal action
('tell the customer to sue them' → blocked_legal with a coaching redirect).
Session-start disclaimer text defined ('This is an AI practice session…').
Selected via PRAXIS_GUARDRAIL=customer_service (default); swaps in for
NoOpGuardrail with no pipeline change (D-019). server/__main__.py loads the
guardrail and logs the disclaimer as the first AI utterance. 9 unit tests
pass (disclaimer, blocks legal/financial/medical, allows normal coaching,
debrief filter blocks 'sue them', debrief allows coaching, swappable with
NoOp).
---ci---
phase: 1
milestone: v0.1
plan: 03
task: 03-04
status: execute
persona: backend-engineer
requirements:
covered: [REQ-ORCH-02, REQ-NFR-SAFE-01]
---/ci---
server/guardrails/noop.py implements the Guardrail interface with an
always-allow stub so the Pipecat pipeline has the pluggable hook from
SLICE-02. Swapping to CustomerServiceGuardrail (SLICE-03 TASK-03-04)
requires no pipeline change (D-019). The session-start disclaimer text
(RESEARCH.md safety baseline) is defined here so the pipeline can play
it as the first AI utterance even before the real ruleset lands.
---ci---
phase: 1
milestone: v0.1
plan: 02
task: 02-07
status: execute
persona: backend-engineer
requirements:
covered: [REQ-ORCH-02]
---/ci---
Praxis CI